Sorting A 2-Dimensional Array on Multiple Axes

Question

I have the following array:

tasks = [["LNWBN","2017-08-13","2017-12-24","Corey","Kyle","Kaleb","Reuben"], 
["NSXEN","2017-08-20","2017-09-18","Kai"], 
["DNMDC","2017-06-19","2017-08-07","Kaleb","Kai","Kyle","Reuben"], 
["UYWEQ","2017-04-23","2017-07-18","Corey","Kyle","Reuben","Kai"], 
["LIVNH","2017-11-01","2017-12-24","Kaleb","Kai"]]

I would like to sort it by the third column followed by the first column so that the result is:

tasks = [["UYWEQ","2017-04-23","2017-07-18","Corey","Kyle","Reuben","Kai"], 
["DNMDC","2017-06-19","2017-08-07","Kaleb","Kai","Kyle","Reuben"], 
["NSXEN","2017-08-20","2017-09-18","Kai"], 
["LIVNH","2017-11-01","2017-12-24","Kaleb","Kai"],
["LNWBN","2017-08-13","2017-12-24","Corey","Kyle","Kaleb","Reuben"]]  

I tried using lexsort:

a = np.array(tasks)
ind = np.lexsort((a[:,2],a[:,0]))    
sorted_tasks = a[ind]

which is the top solution from here Sorting a 2D numpy array by multiple axes but I get the following error:

  ind = np.lexsort((a[:,2],a[:,0]))
IndexError: too many indices for array: array is 1-dimensional, but 2 were indexed

I don't HAVE to use numpy, but that's the only way I found to sort 2D arrays by more than one axis

Appreciate any help.

Answer 1

Why don't you try python's sorted:

sorted(tasks, key=lambda x: (x[2],x[0]))

Output:

[['UYWEQ', '2017-04-23', '2017-07-18', 'Corey', 'Kyle', 'Reuben', 'Kai'],
 ['DNMDC', '2017-06-19', '2017-08-07', 'Kaleb', 'Kai', 'Kyle', 'Reuben'],
 ['NSXEN', '2017-08-20', '2017-09-18', 'Kai'],
 ['LIVNH', '2017-11-01', '2017-12-24', 'Kaleb', 'Kai'],
 ['LNWBN', '2017-08-13', '2017-12-24', 'Corey', 'Kyle', 'Kaleb', 'Reuben']]